There exist a wide range of applications in which it is desirable to determine characteristics of a signal in a substantially automated manner. One such application is data transmission media in general, and for example optical performance monitoring in particular, where it is desirable to identify changes in transmitted optical signals in order to diagnose the cause and location of underlying faults, to optimize the performance of tuneable elements, and to estimate the bit-error rate (BER). Other such applications include sensed biological signals in general, and for example electrocardiogram signal monitoring in particular, where it may be desirable to identify signal characteristics such as the occurrence of, impending onset of, or impending cessation of arrhythmia, fibrillation or other such signal characteristics.
Attempts have been made, with varying levels of success, to identify characteristics of signals based on frequency domain analysis and time domain analysis of the signal in question. Frequency domain methods analyse the spectral content of the signal, and generally average the signal over time and therefore contain little or no information about signal distortion. Time domain signal monitoring techniques sample or obtain a trace of the signal, to produce a representation of the signal waveform. Such time domain techniques are sensitive to signal distortion and noise.
Significant effort has been put into correlating observed signal changes, whether in the frequency domain or time domain, with various signal characteristics. Such signal characteristics could be the result of signal degradation mechanisms arising between the signal source and the point of observation, or could be the result of changes in the signal source itself. However, differentiating between signal characteristics can be difficult, particularly when several characteristics occur simultaneously, as a change in one signal characteristic may cause changes which are to date indiscernible in the observed signal, particularly where the signal is highly complex such as a signal sensed from a biological system. Similarly, changes in different signal characteristics can cause highly similar changes in the signal in question, such that while it may be deduced that some change in the signal has occurred, it may be difficult to determine which signal characteristic out of a plurality of possible characteristics caused the change.
Any discussion of documents, acts, materials, devices, articles or the like which has been included in the present specification is solely for the purpose of providing a context for the present invention. It is not to be taken as an admission that any or all of these matters form part of the prior art base or were common general knowledge in the field relevant to the present invention as it existed before the priority date of each claim of this application.
Throughout this specification the word “comprise”, or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps.